The cloud based distributed data center uses virtualization technology to share the resources to the outside world through a virtual machine. Cloud administrator selects the data center to access virtual machines by using administrative and dynamic policies. Every data center has multiple virtual machines. Selection of data center is an important task which affects on performance as well as cost effectiveness of the data center. This problem can be solved by centralized as well as distributed data center. In Logistics Company, Centralized data center faces bottleneck in operations like virtual machine migration, creation, deletion, and needs to contact central administrator which can increase the negligible amount of network traffic. The paper presents comparison of distributed and centralized data center and strategies of distributed data center for reducing the latency and cost of selection of data center over the cloud by proposing an algorithm distributed service broker policy (DSBP) for logistics information system.
In recent years cloud computing is a very advanced technique to distribute workload among all the data centers and also balance those data center very smoothly. To improve the performance of data centers, load balancing is used to distribute workload of arrival requests on data centers equally in the computing environment. Load balancing has aim to minimize the response time among the users from different data centers and also improve resource utilization by using cloud resources. Cloud based data centers always require efficient load balancing strategies to reduce work load on Virtual Machines (VM). Researchers proposed various load balancing algorithms to optimize different parameters. In this study, we are proposing a distributed service broker policy algorithm which gives better result in centralized and distributed data center environment, considers cloud resources for specific demands and also reduces work load on virtual machines. There are so many VM load balancing algorithms have compared by using different data center broker policies. A cloud analyst simulator, simulate these algorithms and then accurate result will be showed. Experimental results have shown that our proposed Distributed Service Broker Policy (DSBP) algorithm in terms of execution time, response time, throughput, cost as compared to existing round robin, active monitoring and throttled algorithms. The experiments have been done using cloud analyst simulator and comparative analysis is evaluated based on our proposed DSBP algorithm and the results are presented in detail.
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